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valeo.ai

@valeoai.bsky.social
326 followers 45 following 137 posts

We are a research team on artificial intelligence for automotive applications working toward assisted and autonomous driving. --> valeoai.github.io <--

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Andrei Bursuc @abursuc.bsky.social · 06/10/2026
Meet 𝚆𝚑𝚎𝚛𝚎-𝙾𝙿𝙳: a simple strategy to generate synthetic data and tasks for MLLM on-policy self-distillation to improve visual perception. Counting is a super useful skill to have and giving the teacher hints about where to look makes this work.
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Sophia Sirko-Galouchenko 🇺🇦 @ssirko.bsky.social · 05/10/2026
1/n 🚀 New paper 𝚆𝚑𝚎𝚛𝚎-𝙾𝙿𝙳 In on-policy self-distillation, the student learns from a privileged version of itself. In recent methods, privilege often comes from a better view of the image. What if, instead of a better view, the teacher knew where to look? 👀
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ELLIOT Project @elliot-eu.bsky.social · 02/10/2026
How can autonomous driving AI become more efficient? 🚗 🔬We highlight DrivoR by @valeoai.bsky.social, a transformer-based approach that compresses multi-camera information into compact scene representations while supporting safer, more adaptive driving decisions. Read it👉 arxiv.org/pdf/2601.05083
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ELLIOT Project @elliot-eu.bsky.social · 22/09/2026
We were in Barcelona for the Summer School on Autonomous Driving! 🚗 The event explored how AI can support safer, smarter mobility in complex real-world environments. It was great to see so much curiosity, technical exchange and energy in Barcelona. 🤝
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Andrei Bursuc @abursuc.bsky.social · 16/09/2026
We start the 2nd #ssad2026 day with @kashyap7x.bsky.social talking about: Making progress measurable - Evaluation and benchmarking of driving policies
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Andrei Bursuc @abursuc.bsky.social · 16/09/2026
Fatma Güney up next speaking on Learning compact state representations for reliable autonomous driving #ssad2026
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Andrei Bursuc @abursuc.bsky.social · 16/09/2026
The Carla OG German Ros talks about Synthetic data workflows to accelerate AV #ssad2026
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Andrei Bursuc @abursuc.bsky.social · 15/09/2026
José M. Alvarez speaks of End-to-end models for autonomous driving - from direct prediction to counterfactual deliberation on the edge #ssad2026
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Andrei Bursuc @abursuc.bsky.social · 15/09/2026
Maximilian Igl on stage talking about Reinforcement Learning for Autonomous Driving #ssad2026 His slides are available online www.maximilianigl.com/blog/rl-for-...
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Tetiana Martyniuk🇺🇦@ ICIP’26🇫🇮 @t-martyniuk.bsky.social · 16/09/2026
(1/n) Can older lidar SSC models catch up with recent SOTA just by getting better inputs? At #ICIP2026 today and in our new journal extension, we add two cheap priors to existing networks, with no redesign. 📍 Poster #2752, Park Hall, 14:00–16:00 🇫🇮 🧵👇
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valeo.ai @valeoai.bsky.social · 07/09/2026
In Malmö for #ECCV2026? Come find us at the #EmergingAD workshop: 🎤 Oral: September 8, 2026, 11:00, room Malmömässan E2 🖼️ Poster: 14:30-15:30, Malmömässan Exhibit Hall, board #384 Program: emerging-ad.github.io
emerging-ad.github.io
Workshop on Emerging Behaviors in Embodied AI for Achieving Robust Autonomy
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valeo.ai @valeoai.bsky.social · 07/09/2026
Work by @yuanyinnn.bsky.social, E. Ramzi, M. Lafon, V. Charraut, V. Bares, Y. Xu, @eloizablocki.bsky.social, A. Boulch, T. Buhet, @abursuc.bsky.social, @matthieucord.bsky.social 📄 Paper: arxiv.org/abs/2607.26005 🌐 Project page: valeoai.github.io/Pictura #AutonomousDriving #ReinforcementLearning
arxiv.org
Pictura: Perspective-View Self-Play at Scale for Driving
Self-play in simulation produces robust driving policies at scale. Demonstrations of such behavior have been made using privileged vectorized observations such as exact poses and velocities, even for ...
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valeo.ai @valeoai.bsky.social · 07/09/2026
So, can a car learn to drive by playing against itself, cameras only? In simulation, yes. You don't need to assume perception is solved for self-play to work in driving. Train the way you deploy: from pixels. What would you build with a simulator that renders 2M images/s?
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valeo.ai @valeoai.bsky.social · 07/09/2026
How Alberti performs ✅ Approaches its privileged counterpart in-domain in most metrics ✅ Zero-shot transfer to Waymo Open Motion Dataset layouts re-rendered in Pictura ✅ On those unseen layouts it actually BEATS the privileged agents
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valeo.ai @valeoai.bsky.social · 07/09/2026
With Pictura's throughput we trained Alberti: to our knowledge the first large-scale driving self-play policy learned directly from perspective images, no privileged observations, just plain PPO. Training run: 50B agent steps. Roughly 35 million km of driving.
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valeo.ai @valeoai.bsky.social · 07/09/2026
So we made it cheap. Meet Pictura: a GPU-accelerated multi-agent driving simulator that renders each agent's egocentric view at every single step. Up to 500K agent-steps per second. That's 2M images per second. On ONE H100.
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valeo.ai @valeoai.bsky.social · 07/09/2026
Our fix removes it for real: no teacher, just self-play directly from camera views. Why has nobody done this at scale? Because rendering every agent's camera view at every step is brutally expensive.
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valeo.ai @valeoai.bsky.social · 07/09/2026
The usual patch hides the shortcut rather than removing it. Distillation: train a "privileged" policy with perfect information, then teach a camera-only student to imitate it. Problem: the student copies decisions its own view cannot justify, reacting to cars it cannot see.
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valeo.ai @valeoai.bsky.social · 07/09/2026
Can a car learn to drive by playing against itself, using only its cameras? Self-play driving agents have relied on a shortcut: perfect knowledge of every vehicle's position and speed, even the ones they can't see. A real car never gets that. We take the shortcut away. 🧵
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valeo.ai @valeoai.bsky.social · 07/09/2026
How Far Can 5,500 Hours of Driving Take You? A Scaling Law Analysis of Video Diffusion Models tl;dr: we present a systematic scaling-law study of video diffusion models (1M-9B params) on driving data by: V. Besnier, A.Q. Cao & team 📄: arxiv.org/abs/2608.28404
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valeo.ai @valeoai.bsky.social · 07/09/2026
Pictura: Perspective-View Self-Play at Scale for Driving tl;dr: a GPU-accelerated multi-agent driving simulator that renders each agent's egocentric view at every step. by: Y. Yin, E. Ramzi, M. Lafon & team 📄: arxiv.org/abs/2607.26005
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valeo.ai @valeoai.bsky.social · 07/09/2026
CoReDi: Coevolving Representations in Joint Image-Feature Diffusion tl;dr: learning the feature space in joint diffusion image generation models is super handy by: T. Kouzelis, S. Gidaris, N. Komodakis 📄: arxiv.org/abs/2604.17492 x.com/ThKouz/statu...
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valeo.ai @valeoai.bsky.social · 07/09/2026
SSDD: Single-Step Diffusion Decoder for Efficient Image Tokenization tl;dr: novel tokenizer with high compression rate for images in autoencoders by: T. Vallaeys, J. Verbeek, M. Cord 📄: arxiv.org/abs/2510.04961 x.com/webalorn/sta...
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valeo.ai @valeoai.bsky.social · 07/09/2026
Re2Pix: Representations Before Pixels: Semantics-Guided Hierarchical Video Prediction tl;dr: forecast in VFM semantic space first, synthesize pixels second by: E. Karypidis, S. Gidaris, N. Komodakis 📄: arxiv.org/abs/2604.11707 x.com/K_Sta8is/sta...
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valeo.ai @valeoai.bsky.social · 07/09/2026
We’ll be @eccv.bsky.social to present our most recent research! We’ll present three papers in the main conference & two in the Workshops. We will also speak in two workshops & one tutorial. Here is a quick overview on the works we’ll resent in Malmö #eccv2026 valeoai.github.io/posts/eccv-2...
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valeo.ai @valeoai.bsky.social · 27/07/2026
Multiple #ECCV2026 outstanding reviewer awards at @valeoai.bsky.social! Congrats to A. Boulch, @abursuc.bsky.social, @anhquancao.bsky.social, N. Samet, @t-martyniuk.bsky.social, Y. Xu, to our visiting PhD student E. Karypidis, and to our alumnus @gillespuy.bsky.social!
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ELLIOT Project @elliot-eu.bsky.social · 23/07/2026
How can AI better understand 3D driving scenes? 🚗 In this ELLIOT Research Spotlight 🔬, we highlight LOSC from @valeoai.bsky.social: a method for open-vocabulary LiDAR segmentation that helps assign meaning to 3D point clouds, beyond fixed object categories. Paper + code in comments 👇
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valeo.ai @valeoai.bsky.social · 06/07/2026
Everything is out 👇 🌐 Website: alan-lanfeng.github.io/rdm/ 📄 Paper: arxiv.org/abs/2607.02375 🤗 1-step demo: huggingface.co/spaces/epfl-... 💻 Code: github.com/vita-epfl/RDM Led by Lan Feng from EPFL, with Wuyang Li, @eloizablocki.bsky.social, @matthieucord.bsky.social, Alexandre Alahi
alan-lanfeng.github.io
Representation Distribution Matching for One-Step Visual Generation
One step from real. State-of-the-art one-step generation by matching feature distributions, no online teacher, no adversary, no trajectory.
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valeo.ai @valeoai.bsky.social · 06/07/2026
On text-to-image, matching image distributions isn't enough: a model can produce beautiful images while ignoring every prompt. The fix is simply to match the joint (image, caption) law, and prompt fidelity becomes part of the distribution itself.
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valeo.ai @valeoai.bsky.social · 06/07/2026
The recipe also post-trains existing multi-step models into one-step generators. FLUX.2 [klein], a 4-step sampler, becomes 1-step in 90 GPU-hours, and beats its 4-step teacher on GenEval and PickScore. 4x faster, at matched quality
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valeo.ai @valeoai.bsky.social · 06/07/2026
Why 10 encoders? Because we find that matching only one (or a few) can be gamed
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valeo.ai @valeoai.bsky.social · 06/07/2026
Two things make it work: --> Generated side: batches must be huge (>2k+ samples per step, stored w/ gradient caching) --> Real side: all 1.28M ImageNet images compressed once into a frozen Nyström reference
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valeo.ai @valeoai.bsky.social · 06/07/2026
The whole recipe: Generate a large batch of images, embed them with 10 frozen pretrained encoders (DINO, SigLIP, MAE...), and align their feature distribution to match ImageNet's. The loss? A simple MMD.
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valeo.ai @valeoai.bsky.social · 06/07/2026
New state of the art in one-step image generation 🏆 One forward pass. The method is so simple it's almost unsettling: no teacher, no discriminator, no denoising trajectory 🧵
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valeo.ai @valeoai.bsky.social · 03/07/2026
2/ DRIV-EX: Counterfactual Explanations for Driving LLMs Counterfactual explanations: the minimal semantic edit that flips an LLM driving planner's decision. They can expose unexpected biases 📄 arxiv.org/abs/2603.00696 A. Cardiel, @eloizablocki.bsky.social, E. Ramzi, E. Gaussier
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valeo.ai @valeoai.bsky.social · 03/07/2026
1/ Multiple Choice Learning of Low-Rank Adapters for Language Modeling TL;DR: LoRA heads + Winner-Takes-All loss → diverse plausible outputs 📄 arxiv.org/abs/2507.10419 V. Letzelter, H. Malard, M. Fontaine, G. Richard, S. Essid, @abursuc.bsky.social, @ptrkprz.bsky.social
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valeo.ai @valeoai.bsky.social · 03/07/2026
valeo.ai is heading to #ICML2026 and #ACL2026 with two papers: - diverse LLM decoding with LoRA-MCL, - counterfactual explanations for driving LLMs with DRIV-EX 🧵👇
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Andrei Bursuc @abursuc.bsky.social · 19/06/2026
The #WorldEngine tech report is now up! It's our post-training framework to deal w/ scarcity of long-tail safety-critical scenarios. Post-training strategies for autonomous driving are rarely tackled and discussed in the open. We hope that this will open more this area. arxiv.org/abs/2606.19836
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ELLIOT Project @elliot-eu.bsky.social · 09/06/2026
Missed the deadline? You’re in luck! 🚨 👉 Deadline Extended: Friday, 12 June! Last call to dive into robust, multimodal AI for autonomous driving! 🏎️✨ 👇 Apply before Friday! pages.cvc.uab.es/ssadriving/ @ellis.eu @valeoai.bsky.social @uab.cat
pages.cvc.uab.es
ELLIS Summer School on Autonomous Driving — Barcelona 2026
An official ELLIS Summer School — four intensive days in Barcelona where world-class researchers and the next generation of scientists converge to push the boundaries of perception, world models, end-to-end driving, and beyond.
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valeo.ai @valeoai.bsky.social · 03/06/2026
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valeo.ai @valeoai.bsky.social · 03/06/2026
Great event at CVPR in Paris! 🎉 The @valeoai.bsky.social team got to present several posters and had a lot of fun discussions with the community. Thanks to everyone who stopped by!
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valeo.ai @valeoai.bsky.social · 02/06/2026
2/ PPT — pseudo-labeled motion forecasting Pretrain on detecor+tracker trajectories → cross-domain gains. 📄 arxiv.org/abs/2412.06491 💻 github.com/valeoai/ppt Y. Xu, @yuanyinnn.bsky.social, @eloizablocki.bsky.social, @tuanhungvu.bsky.social, @alexandreboulch.bsky.social, M. Cord
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valeo.ai @valeoai.bsky.social · 02/06/2026
1/ R3DPA: LiDAR scene generation via image-prior transfer Aligning gen features w/ self-supervised 3D, transferring RGB priors → SOTA on KITTI-360 📄 arxiv.org/abs/2601.07692 💻 github.com/valeoai/R3DPA N. Sereyjol-Garros, E. Kirby, V. Besnier, N. Samet
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valeo.ai @valeoai.bsky.social · 02/06/2026
The team valeo.ai is at #ICRA2026 in Vienna! 2 papers: one on LiDAR scene generation w/ RGB-pretrained priors, and one on pretraining motion forecasting models from pseudo-labeled trajectories.
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ELLIOT Project @elliot-eu.bsky.social · 01/06/2026
The schedule for the ELLIS Summer School on Autonomous Driving (SSAD 2026) is LIVE! 🏎️✨ 4 days of top-tier AI & robotics research in Barcelona, proudly supported by ELLIOT. ⏳ 7 days left to apply! Secure your spot: 🔗 pages.cvc.uab.es/ssadriving/ @ellis.eu @valeoai.bsky.social @uab.cat
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valeo.ai @valeoai.bsky.social · 01/06/2026
ICM: Attention, May I Have Your Decision? Localizing Generative Choices in Diffusion Models tl;dr: a steering method w/ targeted interventions to a subset of layers to address ambiguous concepts by: K. Zaleska, L. Popek, M. Wysoczanska, K. Deja 📄: arxiv.org/abs/2604.06052
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valeo.ai @valeoai.bsky.social · 01/06/2026
LAM3C: 3D sans 3D Scans: Scalable Pre-training from Video-Generated Point Clouds tl;dr: 3D self-supervised learning without actual 3D scans but from internet videos and VGGT reconstructions by: R. Yamada, K. Ide, Y. Fukuhara, H. Kataoka, G. Puy, . Bursuc, Y. Asano 📄: arxiv.org/abs/2512.23042
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valeo.ai @valeoai.bsky.social · 01/06/2026
LiDAS: Lighting-driven Dynamic Active Sensing for Nighttime Perception tl;dr: HD headlights as active sensors to adaptively focus light in key areas to boost perception in nighttime conditions by: S. de Moreau, A. Bursuc, H. El-Idrissi, F. Moutarde 📄: arxiv.org/abs/2512.08912
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valeo.ai @valeoai.bsky.social · 01/06/2026
StableMTL: Repurposing Latent Diffusion Models for Multi-Task Learning from Partially Annotated Synthetic Datasets tl;dr: denoising framework w/ task encoding, per-task conditioning & a tailored training scheme by: A.Q. Cao, I. Lopes, R. de Charette 📄: arxiv.org/abs/2506.08013
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valeo.ai @valeoai.bsky.social · 01/06/2026
MAD: Motion Appearance Decoupling for efficient Driving World Models tl;dr: efficiently adapt generalist video diffusion models into controllable driving world models w/ minimal supervision by: A. Rahimi, V. Gerard, E. Zablocki, M. Cord, A. Alahi 📄: arxiv.org/abs/2601.09452
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